Generally, the industry of semiconductor manufacturing involves highly complex techniques for integrating circuits into semiconductor materials. Due to the large scale of circuit integration and the decreasing size of semiconductor devices, the semiconductor manufacturing process is prone to processing defects. Testing procedures are therefore critical to maintain quality control. Since the testing procedures are an integral and significant part of the manufacturing process, the semiconductor industry constantly seeks more accurate and efficient testing procedures.
Typical inspection processes detect defects by comparing similar semiconductor device areas on a wafer. The differences detected between the two device areas can either be a defect, which can cause a device to function improperly, or a nuisance, which will not affect system operations. These differences can be referred to as feature differences. It is clear then, that an integral phase of semiconductor wafer inspection involves optimizing the settings, commonly referred to as the “recipe,” of an inspection device so that it can accurately distinguish defects from nuisances.
Typically, semiconductor inspection devices are tuned by using a supplementary review station. FIG. 1 illustrates an exemplary semiconductor inspection system 100 that includes an inspection device 102 that is linked to a review station 104 through a database 106. The circled reference numbers in FIG. 1 describe basic steps of a routine for optimizing the recipe used on inspection device 102. The routine begins at step 1 where inspection device 102, an optical inspector for example, scans the semiconductor wafer, detects feature differences which could be either defects or nuisances, produces large amounts of data concerning these differences, and the person performing the set-up then notes which differences require higher resolution inspection in order to be categorized. Additionally, inspection device 102 produces graphical images, referred to as “patches,” for each of the differences. The patches can have a range of pixel sizes. For example, a patch can be 32×32 or 64×64 pixels in size. At step 2, a subset of the data relating to feature differences that need to be categorized by review station 104 is arranged. This subset of data needs to be sent to review station 104, however, since inspection device 102 and review station 104 typically cannot interoperate smoothly, data transfer between the two devices must be sent via database 106.
Therefore, at step 3, the subset of data is transmitted to database 106 and then at step 4, the data is relayed to review station 104. Review station 104 can be, for example, a scanning electron microscope. At step 5, review station 104 has higher resolution imaging capabilities that are used to categorize the differences that could not be classified on inspection device 102. At step 6, the categorized data is sent back to database 106 and then at step 7, the categorized data is relayed back to inspection device 102. At step 8, inspection device 102 uses the newly categorized information to tune the recipe of inspection device 102. Since only a subset of the data relating to feature differences requiring further categorization was sent to review station 104 in step 3, a second subset of data requiring further categorization is arranged by repeating steps 2–8. This iteration process is repeated until the recipe for inspection device 102 is optimized to the point that inspection results having a desired confidence level is achieved. Once the recipe is optimized, the inspection device 102 is ready for use in a production environment. Generally, confidence levels are increased as the time spent optimizing recipes is increased. However, spending more time on optimization decreases the throughput of semiconductor fabrication processes.
As described in step 2, data transfer between inspection device 102 and review station 104 must go through database 106. This is required because the industry standard data transmission format limits the amount of data that is transmitted between inspection device 102 and review station 104. For example, the transmitted data includes only basic information such as feature difference identification numbers, x and y coordinates for each feature difference, size and defect class code data. Unfortunately, while this information is sent, a large amount of data residing at inspection device 102 cannot be sent to review station 104 for analysis purposes. Therefore, the configuration of the current the inspection systems limit the efficiency of the optimization process by limiting the accessibility of data.
In view of the foregoing, a semiconductor inspection system that can be easily and quickly optimized would be desirable.